tlmakinen
PhD student @ Imperial College @ IAP // prev @ Princeton // working to build probabilistic and deep learning methods for cosmological inference.
Imperial College London + IAPParis, France
Pinned Repositories
21cm-unet
Repository for my senior thesis work with CCA Flatiron and Princeton University Astrophysics
alfi
ALFIL: Automatic Likelihood Free Inference (with IMNN)
cosmicGraphs
Investigating the information content in the cosmic web through dark matter halo graphs. Arxiv paper: https://arxiv.org/abs/2207.05202
deep21
Deep network to separate astrophysical foregrounds from cosmological signal for upcoming 21 cm radio observations. Full paper on arXiv here: https://arxiv.org/abs/2010.15843
hybridStats
For demonstrating experiments for hybrid summary statistics
kosmo-kompress
Code for leveraging Information Maximising Neural Networks for optimal cosmological field compression and Bayesian inference for cosmological parameters
powerbox-jax
Jax implementation of Steven Murray's powerbox: https://github.com/steven-murray/powerbox
pyskim
Repository for Bayesian sparse regression in Jax and NumPyro. Code adapted from https://arxiv.org/abs/1905.06501
sml_515
Repository for graduate course in statistics @Princeton University. Course website: https://princeton.instructure.com/courses/312
snapjax
a fast, flexible SuperNova Analysis Pipeline for Cosmology in Jax
tlmakinen's Repositories
tlmakinen/talks
Repository of public talks
tlmakinen/powerbox-jax
Jax implementation of Steven Murray's powerbox: https://github.com/steven-murray/powerbox
tlmakinen/cosmicFields
clean version of kosmo-kompress
tlmakinen/tlmakinen.github.demo
Repository for my personal pages
tlmakinen/jax-flows
Normalizing Flows in JAX 🌊
tlmakinen/xander
XANDEr: X-ray ANomaly DEtectoR for the Chandra source catalog
tlmakinen/fig_library
tlmakinen/hmf
Python halo mass function calculator
tlmakinen/kosmo-kompress
Code for leveraging Information Maximising Neural Networks for optimal cosmological field compression and Bayesian inference for cosmological parameters
tlmakinen/haloGraphs_scratch
Investigating halo catalog information content with graph network IMNNs
tlmakinen/online-cv
A minimal Jekyll Theme to host your resume (CV)
tlmakinen/jraph-nbody
Simple N-body code in the jraph library
tlmakinen/deep21
Deep network to separate astrophysical foregrounds from cosmological signal for upcoming 21 cm radio observations. Full paper on arXiv here: https://arxiv.org/abs/2010.15843
tlmakinen/MALT
tlmakinen/21cm-unet
Repository for my senior thesis work with CCA Flatiron and Princeton University Astrophysics
tlmakinen/flax
Flax is a neural network library for JAX that is designed for flexibility.
tlmakinen/jraph
A Graph Neural Network Library in Jax
tlmakinen/BAHAMAS-stan
STAN implementation of Bayesian Hierarchical Model for the Analysis of Supernova cosmology (BAHAMAS).
tlmakinen/sml_515
Repository for graduate course in statistics @Princeton University. Course website: https://princeton.instructure.com/courses/312
tlmakinen/pyskim
Repository for Bayesian sparse regression in Jax and NumPyro. Code adapted from https://arxiv.org/abs/1905.06501
tlmakinen/imnn
Code forked from Tom Charnock's awesome IMNN repository: (latest stable version here: https://bitbucket.org/tomcharnock/imnn/src/0.2a5/ ). Working on testing some edge cases in the code. JAX-enabled version on `dev` branch
tlmakinen/pytorch-CycleGAN-and-pix2pix
Image-to-Image Translation in PyTorch
tlmakinen/PPM
Repository for numerical methods in physics class at Sorbonne University (2020-2021)
tlmakinen/CEH
Repository for data analysis for the Center for Evolutionary Hologenomics at the University of Copenhagen.
tlmakinen/powerbox
A python package for making arbitrarily structured, arbitrary-dimension boxes
tlmakinen/BAHAMAS-gibbs
Lighter repository for my work at Imperial College London. Designed to work in the framework of BAyesian HeirArchical Modelling for the Analysis of Supernova Cosmology (BAHAMAS).
tlmakinen/experimental_physics
Repository for my experimental physics class at Princeton University.
tlmakinen/ML-Recon
tlmakinen/supernova_classification
Predicting whether simulated Type Ia supernovae are selected for spectroscopy based on hidden variables. Part of a larger Bayesian hierarchical model for the BAHAMAS inference team at Imperial College London.
tlmakinen/kinetic
Repository for Kinetic Challenge Application